Biology subjects

Sanchez Castellanos, H. M.

Publications and source records attributed to Sanchez Castellanos, H. M..

3 recordsLinked to original sources

bioRxiv2025

Mosquito Dispersal in Context

Mosquito dispersal plays an important role in mosquito ecology and mosquito-borne pathogen transmission. While reaction-diffusion and patch-based models with simple flux assumptions for emigration have played a predominant role in modeling mosquito dispersal, mosquito behavioral ecology - in particular, the process of searching for resources - is usually ignored by diffusion-based models. We thus set out to analyze mosquito movement using highly mimetic models, to see what we could learn from a different approach. Here, we present two behavioral state microsimulation models, in which mosquitoes are in behavioral states and search for required resources, which are distributed on a landscape. Models of this sort are laborious and challenging to work with, so we developed ramp.micro, an R package to build, solve, analyze, and visualize behavioral state microsimulation models for mosquitoes. Mosquito population dispersal is an emergent feature in these complex systems, so we developed new methods to describe and understand it. We show that population structure might not be revealed by a crude analysis of observed mosquito movement patterns, unless it can somehow account for sequences of flights for mosquitoes in behavioral states trying to accomplish a goal. We also show that even when resources are distributed randomly and uniformly, mosquito populations tend to form highly spatially structured communities. We also show that some heterogeneity in mosquito population densities is attributed to features of a network defined by searching and the spatial distribution of resources. These models highlight the importance of understanding mosquito behavioral states and resource availability in understanding mosquito population dispersal, and they point to the importance of local context. Motivated by these dynamics, spatial models for mosquito ecology and mosquito-borne pathogen transmission would benefit from considering resource availability as a factor affecting mosquito movement and dispersal. Author summaryWe develop highly realistic population dynamic models for mosquito behavioral ecology where mosquitoes move around on landscapes made up of resources located at points in space. The mosquitoes are in behavioral states - blood feeding, egg laying, or sugar feeding - and they end each search at a point where the resource they need can be found. Even with simple assumptions, mosquito populations can be highly structured. Because mosquitoes tend to leave areas that lack a resource, and they tend to stay in areas that have all required resources, the scarcest resources end up determining the structure of mosquito populations.

ecology↗

bioRxiv2023

MGSurvE: A framework to optimize trap placement for genetic surveillance of mosquito population

Genetic surveillance of mosquito populations is becoming increasingly relevant as genetics-based mosquito control strategies advance from laboratory to field testing. Especially applicable are mosquito gene drive projects, the potential scale of which leads monitoring to be a significant cost driver. For these projects, monitoring will be required to detect unintended spread of gene drive mosquitoes beyond field sites, and the emergence of alternative alleles, such as drive-resistant alleles or non-functional effector genes, within intervention sites. This entails the need to distribute mosquito traps efficiently such that an allele of interest is detected as quickly as possible - ideally when remediation is still viable. Additionally, insecticide-based tools such as bednets are compromised by insecticide-resistance alleles for which there is also a need to detect as quickly as possible. To this end, we present MGSurvE (Mosquito Gene SurveillancE): a computational framework that optimizes trap placement for genetic surveillance of mosquito populations such that the time to detection of an allele of interest is minimized. A key strength of MGSurvE is that it allows important biological features of mosquitoes and the landscapes they inhabit to be accounted for, namely: i) resources required by mosquitoes (e.g., food sources and aquatic breeding sites) can be explicitly distributed through a landscape, ii) movement of mosquitoes may depend on their sex, the current state of their gonotrophic cycle (if female) and resource attractiveness, and iii) traps may differ in their attractiveness profile. Example MGSurvE analyses are presented to demonstrate optimal trap placement for: i) an Aedes aegypti population in a suburban landscape in Queensland, Australia, and ii)an Anopheles gambiae population on the island of Sao Tome, Sao Tome and Principe. Further documentation and use examples are provided in projects documentation. MGSurvE is freely available as an open-source Python package on pypi (https://pypi.org/project/MGSurvE/). It is intended as a resource for both field and computational researchers interested in mosquito gene surveillance. Author summaryMosquito-borne diseases such as malaria and dengue fever continue to pose a major health burden throughout much of the world. The impact of currently-available tools, such as insecticides and antimalarial drugs, is stagnating, and gene drive-modified mosquitoes are considered a novel tool that could contribute to continuing reductions in disease transmission. Gene drive approaches are unique in the field of vector control in that they involve transgenes that could potentially spread on a wide scale, and consequently, surveillance is expected to be a major cost driver for the technology. This is needed to monitor for unintended spread of intact drive alleles, and the emergence of alternative alleles such as homing-resistance alleles and non-functional effector genes. Additionally, surveillance of insecticide-resistance alleles is of interest to support the impact of insecticide-based tools such as bednets. Here, we present MGSurvE, a computational framework that optimizes trap placement for genetic surveillance of mosquito populations in order to minimize the time to detection for an allele of interest. MGSurvE has been tailored to various features of mosquito ecology, and is intended as a resource for researchers to optimize the efficiency of limited surveillance resources.

bioinformatics↗

bioRxiv2021

Eliminating Aedes aegypti from its southern margin in Australia: insights from genomic data and simulation modeling

A rare example of a successful long-term elimination of the mosquito Aedes aegypti is in Brisbane, Queensland, where the legislatively-enforced removal of rainwater tanks drove its disappearance by the mid-1950s. However, a decade-long drought led to the mass installation of rainwater tanks throughout the region, re-introducing critical breeding sites for the mosquitos persistence in this subtropical region. With Ae. aegypti re-invading towns just 150 km north of Brisbane, we examined the potential for their sustained elimination. Through genomic analyses, we estimated historical expansion and current isolation between neighboring populations as close as 15 kilometers. The estimated recent migration rate, entomological and meteorological data were used to calibrate the simulations of elimination campaigns in the two southernmost populations. Our simulations indicate that Ae. aegypti could be eliminated with moderate release numbers of incompatible Wolbachia-infected (IIT) males (sorted with an error rate [≤]10-6) if non-compliant rainwater tanks are removed first. With this combined campaign, highly effective suppression (>99%) was predicted in both towns, and complete elimination was predicted in 35% of simulations in one town. Without tank removal, however, IIT led to a moderate suppression (61-93%) even with a 40:1 ratio of released IIT males to local males. Moreover, with a ratio of >20:1, Wolbachia establishment was predicted when the sorting error was >10-7. Our conservative estimates of intervention outcomes inform the planning of Ae. aegypti elimination in the region, and offer insight into the effective combinations of conventional and novel control tools, particularly for vulnerable mosquito populations at range margins. SignificanceAfter decades of range stagnation in Australia, the Aedes aegypti mosquito is expanding southward, approaching the most-densely-populated areas of Queensland. Using population genomics and simulation modeling of elimination campaigns, we show that Australias southernmost populations of this disease vector are genetically isolated and could be eliminated with moderate releases of incompatible Wolbachia-infected males if major larval breeding sites (non-compliant rainwater tanks) are removed first. The risk of Wolbachia establishment for this approach is low, and so is the risk of quick mosquito re-invasion. Our conservative estimates of intervention outcomes inform the planning of Ae. aegypti elimination in the region, and offer new insight into the benefits of combining conventional and novel control tools, particularly for mosquito populations at range margins.

systems biology↗